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Results 1 - 10 of 10 for 10x2xf32 (0.23 sec)
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tensorflow/compiler/mlir/lite/tests/prepare-quantize.mlir
%8 = "tfl.concatenation"(%2, %0) {axis = -1 : i32, fused_activation_function = "NONE"} : (tensor<1x1xf32>, tensor<1x1xf32>) -> tensor<1x2xf32> %9 = "quantfork.stats"(%8) {layerStats = dense<[-0.488159984, 0.189515018]> : tensor<2xf32>} : (tensor<1x2xf32>) -> tensor<1x2xf32> %10 = "tfl.concatenation"(%9, %7) {axis = -1 : i32, fused_activation_function = "NONE"} : (tensor<1x2xf32>, tensor<1x2xf32>) -> tensor<1x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 67.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
} func.func @QDQsFollowedByTranspose(tensor<1x2xf32>) -> (tensor<2x1xf32>) { ^bb0(%arg0: tensor<1x2xf32>): %cst_0 = arith.constant dense<[1, 0]> : tensor<2xi32> %0 = "tfl.quantize"(%arg0){qtype = tensor<1x2x!quant.uniform<u8:f32, 1.0>>}: (tensor<1x2xf32>) -> (tensor<1x2x!quant.uniform<u8:f32, 1.0>>) %1 = "tfl.dequantize"(%0): (tensor<1x2x!quant.uniform<u8:f32, 1.0>>) -> (tensor<1x2xf32>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 59.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-post-training.mlir
: ( tensor<1x28x28xf32>, tensor<20x28xf32>, tensor<20x28xf32>, tensor<20x28xf32>, tensor<20x28xf32>, tensor<20x20xf32>, tensor<20x20xf32>, tensor<20x20xf32>, tensor<20x20xf32>, none, none, none, tensor<20xf32>, tensor<20xf32>, tensor<20xf32>, tensor<20xf32>, none, none, tensor<1x20xf32>, tensor<1x20xf32>, none, none, none, none) -> tensor<1x28x20xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 52.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/quantize_composite_functions.mlir
return %2 : tensor<1x2xf32> } func.func private @composite_add_fn(%arg0: tensor<1x2xf32>, %arg1: tensor<1x2xf32>) -> tensor<1x2xf32> attributes {_from_xla_call_module} { %0 = stablehlo.add %arg0, %arg1 : tensor<1x2xf32> %1 = stablehlo.add %0, %arg1 : tensor<1x2xf32> return %1 : tensor<1x2xf32> } } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 05:56:10 UTC 2024 - 91.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_cluster_formation.mlir
// CHECK-SAME: (%[[ARG_0:[a-z0-9]*]]: tensor<!tf_type.resource<tensor<10x3xf32>>>, %[[ARG_1:[a-z0-9]*]]: tensor<!tf_type.resource<tensor<10x3xf32>>>, %[[ARG_2:[a-z0-9]*]]: tensor<!tf_type.resource<tensor<10x3xf32>>>, %[[ARG_3:[a-z0-9]*]]: tensor<!tf_type.resource<tensor<10x3xf32>>>) !rtype = tensor<!tf_type.resource<tensor<10x3xf32>>>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 22:03:30 UTC 2024 - 53.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/lower_tf.mlir
// CHECK-DAG: "tf.ConcatV2"(%[[ITEMS1_3]], %[[ITEMS1_2]], %[[ITEMS1_1]], %[[ITEMS1_0]], %[[ITEMS0_0]], %[[AXIS]]) : (tensor<1x2xf32>, tensor<1x2xf32>, tensor<1x2xf32>, tensor<1x2xf32>, tensor<1x2xf32>, tensor<i64>) -> tensor<5x2xf32> %indices0 = "tf.Const"() {value = dense<4> : tensor<i32>} : () -> tensor<i32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 92K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/lift_quantizable_spots_as_functions.mlir
func.func @dot_general_with_bias_same_shape_fn(%arg0: tensor<1x2xf32>) -> tensor<1x3xf32> { %0 = stablehlo.constant dense<2.000000e+00> : tensor<2x3xf32> %1 = stablehlo.constant dense<2.000000e+00> : tensor<1x3xf32> %2 = stablehlo.dot_general %arg0, %0, contracting_dims = [1] x [0], precision = [DEFAULT, DEFAULT] : (tensor<1x2xf32>, tensor<2x3xf32>) -> tensor<1x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 49.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tensor_array_ops_decomposition.mlir
// CHECK: %[[OLD_SLICE1:.*]] = "tf.Slice"(%[[READ1]], // CHECK: %[[RESHAPE1:.*]] = "tf.Reshape"(%[[VALUE]], // CHECK: %[[ADD1:.*]] = "tf.AddV2"(%[[RESHAPE1]], %[[OLD_SLICE1]]) : (tensor<1x3xf32>, tensor<1x3xf32>) -> tensor<1x3xf32> // CHECK: %[[UPDATE1:.*]] = "tf.XlaDynamicUpdateSlice"(%[[READ1]], %[[ADD1]], // CHECK: "tf.AssignVariableOp"(%[[GVAR1]], %[[UPDATE1]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 49K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.cc
// -> tensor<5x2xf32> // // is lowered to // // %shape = "tf.Const"() {value = dense<[-1, 2]> : tensor<2xi64>} // %inp0 = "tf.Reshape"(%arg0, %shape) // : (tensor<2xf32>, tensor<2xi64>) -> tensor<1x2xf32> // %inp1 = "tf.Reshape"(%arg1, %shape) // : (tensor<2x2x2xf32>, tensor<2xi64>) -> tensor<4x2xf32> // %items0 = "tf.Unpack"(%[[INP0]]) {axis = 0 : i64}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 74.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/g3doc/_includes/tf_passes.md
For example, if we have the code ```mlir %0 = "tf.Const"() {value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %1 = "tf.Const"() {device = "", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %2 = "tf.Const"() {device = "baz", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> ``` then running this pass with 'default-device=foobar', we get: ```mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Aug 02 02:26:39 UTC 2023 - 96.4K bytes - Viewed (0)